That's a wrap! If you are interested in any of these topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
@sumanth_077
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Project-Based Learning: Implement Concepts with Real-World Use Cases
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3. Project-Based Learning: Learning the concepts is great, but implementing them for real-world use cases will get your hands dirty. Check out the below repo. Also, leverage LLMs like ChatGPT and Claude 3.5 Sonnet to learn and build things quickly. https://
github.com/practical-tuto
rials/project-based-learning?tab=readme-ov-file#python
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Corey Schafer: Best YouTube Channel for Learning Python
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2. Corey Schafer Best YouTube channel to learn Python! Corey explains every pythonconcept from scratch along with project based implementation. Check it out:
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Microsoft Launches Free 18-Lesson Generative AI Course on GitHub
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Microsoft launched the best course on Generative AI! The free 18 lesson course is available on Github and will teach you everything you need to know to start building Generative AI applications.
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Daily Content on Python, Data Science, Machine Learning, and LLMs
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That's a wrap! If you are interested in any of these topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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RAPIDS cuDF Library Now Integrated into Google Colab
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Also their cuDF library will automatically know if you're running on GPU or CPU and speed up your processing. RAPIDS cuDF is now integrated directly into Google Colab. Checkout the Colab Notebook: https://
colab.research.google.com/github/rapidsa
i-community/showcase/blob/main/getting_started_tutorials/cudf_pandas_colab_demo.ipynb?ncid=ref-inor-594904
… Check out the Github Repo: -
cuDF Pandas Accelerator: Accelerated Computing for Large Datasets
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Pandas operates in-memory, as it loads the entire dataset into the local memory of the machine it is running on. This limits its ability to handle large datasets. With cuDF’s pandas accelerator you can now bring accelerated computing to pandas workflows.
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NVIDIA accelerates Pandas 150x faster with minimal code changes
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Pandas is a powerful data analysis and manipulation library for Python!
— Sumanth (@Sumanth_077) 26 juin 2024
NVIDIA just made Pandas 150x faster with zero code changes🔥
All you have to add is just a couple of lines of code:
%load_ext cudf.pandas
import pandas as pd pic.twitter.com/5JKqte1tppPandas is a powerful data analysis and manipulation library for Python! NVIDIA just made Pandas 150x faster with zero code changes All you have to add is just a couple of lines of code: %load_ext cudf.pandas
import pandas as pd -
Daily Content on Python, Data Science, Machine Learning, and MLOps
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That's a wrap! If you are interested in any of these topics: – Python – Data Science – Machine Learning – Data Analysis – LLMs – MLOps Find me → @Sumanth_077 I'm sharing daily content over here.
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Chat with Your Data: Summarizing PDF Files
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Step 4: Chat with your data Finally, once the data has been ingested into the app, chat with your data. Here we are asking it to summarize the pdf file.